Protection, energetic assistance, or social perks: How do beluga offspring benefit from allocare?
Bibliographic record
Abstract
Abstract Allocare, care for offspring from nonparents, can carry important benefits for offspring. We investigated the potential benefits of allocare to offspring by examining contexts associated with allocare among St. Lawrence belugas in Sainte‐Marguerite Bay, a high‐residency area, and the Saguenay Fjord, a transit area. We hypothesized that calves receive similar benefits from mothers and alloparents, namely, protection and energetic benefits, while juveniles associate with alloparents for social purposes. As such, we expected that calves would associate with mothers and alloparents more frequently when exposed to potential dangers, such as adult males and vessel traffic, and in energetically costly contexts, such as the flood tide and during travel, while juveniles would associate with alloparents more frequently during social behavior. We found no trends between allocare and any variables tested. However, we found that calf maternal care in the fjord decreased significantly during socialization, particularly calf‐calf socialization. We also found that juvenile maternal care in the fjord decreased significantly when males were present, possibly because juveniles sought associations with males. These findings emphasize the importance of socialization for beluga offspring of all ages. Both maternal care and allocare persisted across contexts in Sainte‐Marguerite Bay, highlighting its possible importance as an offspring‐rearing ground.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".